DOCUMENTATION ON LINEAR REGRESSION
Linear Regression Linear Regression is the simplest algorithm . Linear Regression is basically modelled using a straight line . It is used with continous variable to predict values . It is illustrated by the equation : y= a0+a1x+ ε This equation tells us the relationship b/w the two variables i.e x and y. y depends on the value of x . and where,a0 is the intercept ,a1 is Linear regression coefficient and ε = random error. Types Positive and Negative Linear Relationship: In Positive linear relationship, if y increases then x increases. In Negative linear relationship, if y decreases then x decreases. Our main aim in this regression is to find the best fitted line . So, basically there are three common evolution metrics to find that : Mean Absolute Error Mean Squared Error Root Mean Squared Error Linear regression is furture categorized into two types of the algorithm: Simple Linear Regression: If only one variable(...